UC Davis Institute of Transportation Studies

Using data collected from 164 French employees of a transportation institute and 1904 residents of the U.S. San Francisco Bay Area, we operationalize a segmentation of mobility patterns based on objective, subjective, and desired amounts of mobility by various modes and overall. We define a multimodality index from basic concepts of information theory, and we especially focus on the degree of multimodality in an individual’s current modal mix and desired changes to that mix. The clusters that result showed some similarities and some differences across countries, where the latter are likely due to disparities in the sampling strategies and in the land use/transportation/ cultural milieux. In both cases, however, the clusters have useful policy implications, enabling us, for example, to distinguish car users who might be inclined to reduce car use and increase transit use from those who are largely content with their current modal baskets.